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• A stiffness optimization method for plane-mobile robot in automated fiber placement (AFP) is proposed.
• A stiffness index based on contact force characteristics is proposed to evaluate the comprehensive stiffness of AFP robot.
• An ...

The low stiffness of series robots limits their application in high-load precision manufacturing, such as automated fiber placement (AFP). This paper presents a stiffness optimization method to enhance the stiffness of plane-mobile robots in ...

In this work, we aim to achieve room-level localization for mobile robots in industrial workshops. It is difficult to obtain precise localization information via common methods because of the complexity of the industrial environment. Our findings ...

For the challenges of low learning efficiency, slow convergence speed and slow inference speed in robot path planning. This paper proposes an improved deep reinforcement learning algorithm for robot path planning. Firstly, the Dueling DQN network ...$$

Mobile robots are being used more widely in various environments, such as households, hospitals, agriculture, and industry. In these spaces, many times the robots are required to cover long distances, at times carrying heavy payloads, resulting in ...

This study focuses on applying the algorithm of Dueling Double Deep Q Networks to create a robust and adaptable navigation system for autonomous robots. The main objective of the study is to propose a network model that is capable of making a ...

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• Enables a mobile robot to navigate to specified targets in unknown environments.
• Has a complex reward function for time reduction and orientation adjustment.
• Includes dynamic and static obstacles with real-world data to increase ...

This paper proposes a novel path planning algorithm called Reference Linguistic Fuzzy Algorithm (RLFA); moreover, the parametric analysis procedure of the RLFA is described in this paper. It finds the optimal path by calculating the decision value ...

With the gradual expansion of robot applications, the operating environment is becoming more and more complex, and various uncertainty may be encountered. Investigating how to efficiently respond to various uncertainty in the environment has ...

This study uses PID (Proportional-Integral-Derivative), fuzzy logic, and deep learning algorithm to experimentally achieve real-time position control of a four-wheel-drive symmetric autonomous mobile robot whose design and prototype are realized. ...

With the development of the power system, the number of substation equipment continues to increase, and the use of intelligent mobile robots to replace traditional manual inspection methods is a trend, which can improve inspection efficiency and ...

Effective integration of multi-sensor measurements is crucial for mobile robot fault diagnosis. However, in multi-sensor relationship modeling, existing methods often neglect the impact of different fault types and fail to consider the relations ...

Several studies have proposed that mobile robots can indicate their movement direction by displaying arrows to facilitate smooth passing of humans. However, the interpretation of these arrows can be ambiguous, as they are also commonly used as ...

• Design three path planning methods for mobile robots.
• Combining the ACO algorithm and the improved artificial potential field method.
• Improve the ant colony algorithm through firefly algorithm and heuristic function.
• Provide ...

The rapid development of robotics technology has driven the growth of robot types and the development of related technologies. As an important aspect of robot research, path planning technology plays an irreplaceable role in practical production ...

The genetic algorithm (GA) is a well-known meta-heuristic technique for addressing the static mobile robot global path planning (MRGPP) issue. Current GA, however, has certain shortcomings, such as inefficient population initialization and low-...

• Proposed an enhanced GA for mobile robot global route planning.
• Introduced a novel population initialization method based on fitness score.
• Combined various genetic operators to balance global and local search.
• Compared the ...

As one of fundamental problems in robotics, coverage path planning (CPP) requires the robot path to cover the entire workspace which has been employed in several essential applications such as cleaning robots, land mine detector, lawnmowers and ...

• This paper tackles coverage path planning with energy constraints.
• It introduces BWave, a novel framework for complete coverage.
• BWave has two phases: environment knowledge extracting and complete coverage.
• BWave is evaluated ...

Aiming at the shortcomings of traditional A* algorithm planning such as long path calculation time, multiple search nodes, and multiple turning points, an improved A* algorithm based on weight coefficient optimization is proposed. By comparing ...

• A novel mobile robot is designed to remove debris from high-voltage power lines.
• A novel mobile robot that can be integrated with a drone for transportation.
• A mobile robot was developed and tested in high-voltage power lines up to ...

The importance of electrical energy in human life has grown considerably, resulting in a great surge in demand for this energy form. As a consequence, numerous power transmission lines are continuously under construction. Periodic inspections and ...

In order to shorten searching time and reduce the quantity of redundant nodes in path planning, an improved A* algorithm was proposed. In the novel algorithm, compared with the A* algorithm, the octet neighborhood was replaced a rectangular ...

• The map was rectangle explored in two directions.
• A new method was designed to seek the best search node.
• the adaptive cost function was adopted to improve the safety.
• A Slide-Rail corner adjustment method was designed to get ...

Aiming at the problem of trajectory tracking control for mobile robot nonlinear systems with non-repetitive uncertain parameters, we propose a novel neural network compensator-based robust iterative learning control (NNRILC) scheme to achieve ...

• A novel ILC scheme combining neural network compensator is designed to solve trajectory tracking problem.
• The Runge-Kutta algorithm is introduced to solve the state differential equation and the controller equation.
• A neural ...

In order to realize the visual navigation of mobile robots in e-commerce logistics scenarios, a target detection method for mobile robot based on precision of Faster R-CNN for small targets and complex environments is improved by replacing the backbone ...

This research aims to design controllers based on the hedge-algebras (HA) theory to control differential robots that track reference trajectories. First, the HA-based controller (denoted as HA controller) is synthesized by selecting a suitable ...